News

Dilakshan received People’s Choice award at NAGS 3MT

Dilakshan received People’s Choice award at NAGS 3MT

Dilakshan Srikanthan represented Queen's University at the NAGS 3-Minute Thesis Competition this year and received the People's Choice award for his outstanding presentation. More information on NAGS 3MT can be found on Northeastern Association of Graduate Schools and School of Graduate Studies and Postdoctoral Affairs websites.

Med-i CREATE Summer Competition Winners Announced

Med-i CREATE program recently held its Annual Summer Competition, providing trainees with the opportunity to apply for funding by submitting research proposals to hire summer students. This year, five Med-i CREATE trainees were selected as winners. Each of these trainees will have the opportunity to mentor an undergraduate student in the summer term, guiding them in accomplishing tasks related to...
Congratulations to Mahdi Gilany on Successfully Completing the Ph.D. Defense

Congratulations to Mahdi Gilany on Successfully Completing the Ph.D. Defense

Med-i CREATE trainee Mahdi Gilany successfully defended his thesis titled "Towards High-Fidelity Prostate Tissue Characterization and Cancer Detection with Micro-Ultrasound and Deep Learning," Congratulations Mahdi!
Outstanding Achievements by Med-i CREATE Students at ImNO 2025

Outstanding Achievements by Med-i CREATE Students at ImNO 2025

We are thrilled to announce that four Med-i CREATE students Vivian Nguyen, Laura Connolly, Kaito Hara-Lee and Bining Long have won Best Presentation awards in their respective sessions at the prestigious IGT x Imaging Network of Ontario (ImNO) 2025 Conference. The IGT x ImNO Joint Symposium was held in Toronto on March 5-6. Congratulations to all of them for their...

Projects

Integration, federation, and retrieval of large-scale data repositories in Canada

We collaborate with the Canadian Institute of Health Information (CIHI) and the Ontario Health Data Platform (OHDP) to tackle novel challenges in data management and devise evaluation frameworks that center on security, performance and fairness.

Next generation of actionable prescriptive analysis using multi-resolution, multi-modality data

We build computation models of disease from multi-omics data using machine learning, deep learning and evolutionary algorithms, focusing on innovations that address the unique nature of health data and the unavailability and vagueness of gold-standard labels (e.g., pathology labels).

Democratization of AI, software and data for healthcare

We're international leaders in developing and disseminating open source software using low-cost point-of-care imaging. Our positive impact on the global computer–assisted medical interventions community has is constantly expanding. We'll meet new challenges for discovery, refinement of methods and innovative AI-powered solutions using large open source data, hence democratizing access to care and positive outcomes of AI.